docs: def unique(arr, tolerance=1e-6) -> np.ndarray:
      """Return unique elements in 1D array, within tolerance.
  
      Parameters
      ----------
      arr : array_like
          Input array. This will be flattened if it is not already 1D.
      tolerance : number (optional)
          The tolerance for uniqueness.
  
      Returns
      -------
      array
          The sorted unique values.
      """
      arr = sorted(arr.flatten())
      unique = []
      while len(arr) > 0:
          current = arr[0]
          lis = [xi for xi in arr if np.abs(current - xi) < tolerance]
          arr = [xi for xi in arr if not np.abs(lis[0] - xi) < tolerance]
          xi_lis_average = sum(lis) / len(lis)
          unique.append(xi_lis_average)
      return np.array(unique)